{"id":"W3093147335","doi":"10.1016/j.fertnstert.2020.08.425","title":"AUTOMATIC IMAGE SEGMENTATION AND QUANTITATIVE COMPONENT MEASUREMENTS ON HUMAN BLASTOCYST IMAGES USING ARTIFICIAL INTELLIGENCE (AI) IN ASSESSING MORPHOLOGY GRADING AND PREDICTING IMPLANTATION AND LIVE BIRTH OUTCOMES","year":2020,"lang":"en","type":"article","venue":"Fertility and Sterility","topic":"Reproductive Biology and Fertility","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; Pacific Centre for Reproductive Medicine","funders":"","keywords":"Blastocyst; Zona pellucida; Confidence interval; Inner cell mass; Segmentation; Blastocoel; Andrology; Biology; Medicine; Embryo; Artificial intelligence; Computer science; Internal medicine; Embryogenesis; Oocyte; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007994412,0.0003079409,0.0002843333,0.001813512,0.0001645831,0.0007040707,0.0003019555,0.000617952,0.0006469526],"category_scores_gemma":[0.001682367,0.000179895,0.0003047963,0.000841788,0.0002501226,0.0002904769,0.0002397621,0.0002540101,0.0002272656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000207704,"about_ca_system_score_gemma":0.0003535121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00291399,"about_ca_topic_score_gemma":0.003360387,"domain_scores_codex":[0.9997471,0.00007504114,0.00002258124,0.00005584152,0.0000729775,0.00002651062],"domain_scores_gemma":[0.9993619,0.0002645012,0.00006394329,0.00004173873,0.0002315264,0.00003635208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001849402,0.0002714458,0.07329749,0.0003859657,0.0001704103,0.0003507926,0.0003362102,0.01912497,0.3327111,0.001054873,0.001333442,0.5691139],"study_design_scores_gemma":[0.00004843541,0.0005184132,0.2286458,0.0000767746,0.000294796,0.0009700375,0.0003765509,0.6523114,0.1135801,0.001297692,0.001798458,0.00008153215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7499846,0.001423126,0.2441233,0.0001877825,0.00007742477,0.000223886,0.0004824924,0.0008495718,0.002647797],"genre_scores_gemma":[0.9029964,0.000430819,0.09518282,0.00006316025,0.00002501532,0.00007742999,0.0002726061,0.00004255927,0.000909182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00291399,"threshold_uncertainty_score":0.005794108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2056224012590058,"score_gpt":0.4059830172627427,"score_spread":0.2003606160037369,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}